kld_adaptive_particle_filter.hpp

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#ifndef PCL_TRACKING_IMPL_KLD_ADAPTIVE_PARTICLE_FILTER_H_
#define PCL_TRACKING_IMPL_KLD_ADAPTIVE_PARTICLE_FILTER_H_

#include <pcl/tracking/kld_adaptive_particle_filter.h>

template <typename PointInT, typename StateT> bool
pcl::tracking::KLDAdaptiveParticleFilterTracker<PointInT, StateT>::initCompute ()
{
  if (!Tracker<PointInT, StateT>::initCompute ())
  {
    PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
    return (false);
  }

  if (transed_reference_vector_.empty ())
  {
    // only one time allocation
    transed_reference_vector_.resize (maximum_particle_number_);
    for (unsigned int i = 0; i < maximum_particle_number_; i++)
    {
      transed_reference_vector_[i] = PointCloudInPtr (new PointCloudIn ());
    }
  }
  
  coherence_->setTargetCloud (input_);

  if (!change_detector_)
    change_detector_ = boost::shared_ptr<pcl::octree::OctreePointCloudChangeDetector<PointInT> >(new pcl::octree::OctreePointCloudChangeDetector<PointInT> (change_detector_resolution_));
  
  if (!particles_ || particles_->points.empty ())
    initParticles (true);
  return (true);
}

template <typename PointInT, typename StateT> bool
pcl::tracking::KLDAdaptiveParticleFilterTracker<PointInT, StateT>::insertIntoBins
(std::vector<int> bin, std::vector<std::vector<int> > &B)
{
  for (size_t i = 0; i < B.size (); i++)
  {
    if (equalBin (bin, B[i]))
      return false;
  }
  B.push_back (bin);
  return true;
}

template <typename PointInT, typename StateT> void
pcl::tracking::KLDAdaptiveParticleFilterTracker<PointInT, StateT>::resample ()
{
  unsigned int k = 0;
  unsigned int n = 0;
  PointCloudStatePtr S (new PointCloudState);
  std::vector<std::vector<int> > B; // bins
  
  // initializing for sampling without replacement
  std::vector<int> a (particles_->points.size ());
  std::vector<double> q (particles_->points.size ());
  this->genAliasTable (a, q, particles_);
  
  const std::vector<double> zero_mean (StateT::stateDimension (), 0.0);
  
  // select the particles with KLD sampling
  do
  {
    int j_n = sampleWithReplacement (a, q);
    StateT x_t = particles_->points[j_n];
    x_t.sample (zero_mean, step_noise_covariance_);
    
    // motion
    if (rand () / double (RAND_MAX) < motion_ratio_)
      x_t = x_t + motion_;
    
    S->points.push_back (x_t);
    // calc bin
    std::vector<int> bin (StateT::stateDimension ());
    for (int i = 0; i < StateT::stateDimension (); i++)
      bin[i] = static_cast<int> (x_t[i] / bin_size_[i]);
    
    // calc bin index... how?
    if (insertIntoBins (bin, B))
      ++k;
    ++n;
  }
  while (k < 2 || (n < maximum_particle_number_ && n < calcKLBound (k)));
  
  particles_ = S;               // swap
  particle_num_ = static_cast<int> (particles_->points.size ());
}


#define PCL_INSTANTIATE_KLDAdaptiveParticleFilterTracker(T,ST) template class PCL_EXPORTS pcl::tracking::KLDAdaptiveParticleFilterTracker<T,ST>;

#endif